code: def forward(
      self, embedded_tokens: torch.Tensor, padding_mask: torch.Tensor
  ):
      all_layers = self.extract_features(
          embedded_tokens, padding_mask
      )  # list of [T x B x C]
      return [layer.transpose(0, 1) for layer in all_layers]
  
imports: import re
  from typing import List, Optional
  import torch
  from pytext.utils.usage import log_class_usage
  from pytorch.text.fb.nn.modules.transformer import Transformer
  from torch import nn
label_desc: Use image node_id 1 for calling the PassthroughEncoder obj's underlying member method code with example usage: obj.forward(embedded_tokens, padding_mask) and returns: unknown